17 papers · 1 filter
DRIFT: Difficulty-aware Rectified Flows for Through-plane MRI Super-Resolution
Yoonseok Choi, Eun-Gyu Ha, Daniel Kim +3
Magnetic Resonance Imaging (MRI) is often acquired with anisotropic resolution to reduce scan time, producing stair-step artifacts along the through-plane direction. In through-pla…
Controlling Motion Transfer in Diffusion Transformers via Attention Heads
Sunyoung Jung, Jiwoo Park, Yoonseok Choi +3
Diffusion Transformers (DiTs) have advanced video generation with high-quality, temporally coherent results. However, extending them to motion transfer, which requires following re…
Layer-Aware Video Composition via Split-then-Merge
Ozgur Kara, Yujia Chen, Ming-Hsuan Yang +3
We present Split-then-Merge (StM), a novel framework designed to enhance control in generative video composition and address its data scarcity problem. Unlike conventional methods…
Scaling Laws for Deepfake Detection
Wenhao Wang, Longqi Cai, Taihong Xiao +2
This paper presents a systematic study of scaling laws for the deepfake detection task. Specifically, we analyze the model performance against the number of real image domains, dee…
SceneAdapt: Scene-aware Adaptation of Human Motion Diffusion
Jungbin Cho, Minsu Kim, Jisoo Kim +5
Human motion is inherently diverse and semantically rich, while also shaped by the surrounding scene. However, existing motion generation approaches fail to generate semantically d…
From Prompt to Progression: Taming Video Diffusion Models for Seamless Attribute Transition
Ling Lo, Kelvin C. K. Chan, Wen-Huang Cheng +1
Existing models often struggle with complex temporal changes, particularly when generating videos with gradual attribute transitions. The most common prompt interpolation approach…